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A Novel Eccentric Intrusion Detection Model Based on Recurrent Neural Networks with Leveraging LSTM

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Computers, Materials & Continua 2024年第3期78卷 3089-3127页

作者： Navaneetha Krishnan Muthunambu Senthil Prabakaran Balasubramanian Prabhu Kavin Kishore Senthil Siruvangur Kavitha Chinnadurai Jehad Ali Department of Computer Applications Karpagam College of EngineeringCoimbatore641032India Department of Computer Science and Engineering Karpagam College of EngineeringCoimbatore641032India Department of Data Science and Business Systems College of Engineering and TechnologySRM Institute of Science and TechnologyKattankulathur603203India Department of Computer Science and Engineering Sathyabama Institute of Science and TechnologyJeppiaar NagarRajiv Gandhi SalaiChennai600119India Department of AI Convergence Network Ajou UniversitySuwon16499Korea

The extensive utilization of the Internet in everyday life can be attributed to the substantial accessibility of online services and the growing significance of the data transmitted via the ***,this development has expanded the potential targets that hackers might *** adequate safeguards,data transmitted on the internet is significantly more susceptible to unauthorized access,theft,or *** identification of unauthorised access attempts is a critical component of cybersecurity as it aids in the detection and prevention of malicious *** research paper introduces a novel intrusion detection framework that utilizes Recurrent Neural Networks(RNN)integrated with Long Short-Term Memory(LSTM)*** proposed model can identify various types of cyberattacks,including conventional and distinctive *** networks,a specific kind of feedforward neural networks,possess an intrinsic memory *** Neural Networks(RNNs)incorporating Long Short-Term Memory(LSTM)mechanisms have demonstrated greater capabilities in retaining and utilizing data dependencies over extended *** such as data types,training duration,accuracy,number of false positives,and number of false negatives are among the parameters employed to assess the effectiveness of these models in identifying both common and unusual *** are utilised in conjunction with LSTM to support human analysts in identifying possible intrusion events,hence enhancing their decision-making capabilities.A potential solution to address the limitations of Shallow learning is the introduction of the Eccentric Intrusion Detection *** model utilises Recurrent Neural Networks,specifically exploiting LSTM *** proposed model achieves detection accuracy(99.5%),generalisation(99%),and false-positive rate(0.72%),the parameters findings reveal that it is superior to state-of-the-art techniques.

关键词： Cybersecurity intrusion detection machine learning leveraging long short-term memory(LLSTM) CICIDS2019 dataset innovative cyberattacks

An Empirical Study on the Effectiveness of Adversarial Examples in Malware Detection

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 3535-3563页

作者： Younghoon Ban Myeonghyun Kim Haehyun Cho School of Software Soongsil UniversitySeoul06978Korea

Antivirus vendors and the research community employ Machine Learning(ML)or Deep Learning(DL)-based static analysis techniques for efficient identification of new threats,given the continual emergence of novel malware *** the other hand,numerous researchers have reported that Adversarial Examples(AEs),generated by manipulating previously detected malware,can successfully evade ML/DL-based *** antivirus systems,in particular,have been identified as vulnerable to such *** paper firstly focuses on conducting black-box attacks to circumvent ML/DL-based malware *** attack method utilizes seven different perturbations,including Overlay Append,Section Append,and Break Checksum,capitalizing on the ambiguities present in the PE format,as previously employed in evasion attack *** directly applying the perturbation techniques to PE binaries,our attack method eliminates the need to grapple with the problem-feature space dilemma,a persistent challenge in many evasion attack *** a black-box attack,our method can generate AEs that successfully evade both DL-based and ML-based ***,AEs generated by the attack method retain their executability and malicious behavior,eliminating the need for functionality *** thorogh evaluations,we confirmed that the attack method achieves an evasion rate of 65.6%against well-known ML-based malware detectors and can reach a remarkable 99%evasion rate against well-known DL-based malware ***,our AEs demonstrated the capability to bypass detection by 17%of vendors out of the 64 on VirusTotal(VT).In addition,we propose a defensive approach that utilizes Trend Locality Sensitive Hashing(TLSH)to construct a similarity-based defense *** several experiments on the approach,we verified that our defense model can effectively counter AEs generated by the perturbation *** conclusion,our defense model alleviates the limitation of the mos

关键词： Malware classification machine learning adversarial examples evasion attack cybersecurity

A Novel Framework to Construct S-Box Quantum Circuits Using System Modeling: Application to 4-Bit S-Boxes

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Computer Modeling in Engineering & Sciences 2024年第10期141卷 545-561页

作者： Yongjin Jeon Seungjun Baek Jongsung Kim Department of Financial information Security Kookmin UniversitySeoul02707Republic of Korea

Quantum computers accelerate many algorithms based on the superposition principle of quantum *** Grover algorithm provides significant performance to malicious users attacking symmetric key *** the performance of attacks using quantum computers depends on the efficiency of the quantum circuit of the encryption algorithms,research research on the implementation of quantum circuits is *** paper presents a new framework to construct quantum circuits of substitution boxes(S-boxes)using system *** model the quantum circuits of S-boxes using two layers:Toffoli and linear *** generate vector spaces based on the values of qubits used in the linear layers and apply them to find quantum *** framework finds the circuit bymatching elements of vector spaces generated fromthe input and output of a given S-box,using the forward search or themeet-in-the-middle *** developed a tool to apply this framework to 4-bit *** the 4-bit S-box quantum circuit construction tool LIGHTER-R only finds circuits that can be implemented with four qubits,the proposed tool achieves the circuits with five *** proposed tool can find quantum circuits of 4-bit odd permutations based on the controlled NOT,NOT,and Toffoli gates,whereas LIGHTER-R is unable to perform this task in the same *** expect this technique to become a critical step toward optimizing S-box quantum circuits.

关键词： System modeling quantum circuit S-box circuit quantum computer

Block Incremental Dense Tucker Decomposition with Application to Spatial and Temporal Analysis of Air Quality Data

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 319-336页

作者： SangSeok Lee HaeWon Moon Lee Sael Department of Artificial Intelligence Ajou UniversitySuwon-si16499Korea Department of Software and Computer Engineering Ajou UniversitySuwon-si16499Korea

How can we efficiently store and mine dynamically generated dense tensors for modeling the behavior of multidimensional dynamic data?Much of the multidimensional dynamic data in the real world is generated in the form of time-growing *** example,air quality tensor data consists of multiple sensory values gathered from wide locations for a long *** data,accumulated over time,is redundant and consumes a lot ofmemory in its raw *** need a way to efficiently store dynamically generated tensor data that increase over time and to model their behavior on demand between arbitrary time *** this end,we propose a Block IncrementalDense Tucker Decomposition(BID-Tucker)method for efficient storage and on-demand modeling ofmultidimensional spatiotemporal *** that tensors come in unit blocks where only the time domain changes,our proposed BID-Tucker first slices the blocks into matrices and decomposes them via singular value decomposition(SVD).The SVDs of the time×space sliced matrices are stored instead of the raw tensor blocks to save *** modeling from data is required at particular time blocks,the SVDs of corresponding time blocks are retrieved and incremented to be used for Tucker *** factor matrices and core tensor of the decomposed results can then be used for further data *** compared our proposed BID-Tucker with D-Tucker,which our method extends,and vanilla Tucker *** show that our BID-Tucker is faster than both D-Tucker and vanilla Tucker decomposition and uses less memory for storage with a comparable reconstruction *** applied our proposed BID-Tucker to model the spatial and temporal trends of air quality data collected in South Korea from 2018 to *** were able to model the spatial and temporal air quality *** were also able to verify unusual events,such as chronic ozone alerts and large fire events.

关键词： Dynamic decomposition tucker tensor tensor factorization spatiotemporal data tensor analysis air quality

NOON-state interference in the frequency domain

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Light(Science & Applications) 2024年第5期13卷 843-851页

作者： Dongjin Lee Woncheol Shin Sebae Park Junyeop Kim Heedeuk Shin Department of Physics Pohang University of Science and Technology(POSTECH)Pohang 37673South Korea

The examination of entanglement across various degrees of freedom has been pivotal in augmenting our understanding of fundamental physics,extending to high dimensional quantum states,and promising the scalability of quantum *** this paper,we demonstrate the photon number path entanglement in the frequency domain by implementing a frequency beam splitter that converts the single-photon frequency to another with 50%probability using Bragg scattering four-wave *** two-photon NOON state in a single-mode fiber is generated in the frequency domain,manifesting the two-photon interference with two-fold enhanced resolution compared to that of single-photon interference,showing the outstanding stability of the *** successful translation of quantum states in the frequency domain will pave the way toward the discovery of fascinating quantum phenomena and scalable quantum information processing.

关键词： quantum state showing

Intelligent reflecting surface for sum rate enhancement in MIMO systems

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Digital communications and Networks 2024年第1期10卷 94-100页

作者： Chan-Yeob Park Ji-Sung Jung Yeong-Rong Lee Beom-Sik Shin Hyoung-Kyu Song Department of information and Communication Engineering Sejong UniversitySeoulGwangjin-guGunja-dong 98Republic of Korea Department of Convergence Engineering for Intelligent Drone Sejong University SeoulGwangjin-guGunja-dong 98Republic of Korea

The research for the Intelligent Reflecting Surface(IRS)which has the advantages of cost and energy efficiency has been *** capacity can be effectively increased by appropriately setting the phase value of IRS elements according to the channel ***,the problem of obtaining an appropriate phase value of IRs is difficult to solve due to the non-convex *** paper proposes an iterative algorithm for the alternating optimal solution in the Single User Multiple-Input-Multiple-Output(SU-MIMO)*** proposed iterative algorithm finds an alternating optimal solution that is the phase value of IRS one by *** results show that the proposed method has better performance than that of the randomized IRS *** number of iterations for maximizing the performance of the proposed algorithm depends on the channel state between the IRS and the receiver.

关键词： Intelligent reflecting surface MIMO Sum rate

A Framework for Enhancing Privacy and Anonymity in Blockchain-Enabled IoT Devices

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Computers, Materials & Continua 2024年第3期78卷 4263-4282页

作者： Muhammad Saad Muhammad Raheel Bhutta Jongik Kim Tae-Sun Chung Department of Artificial Intelligence Ajou UniversitySuwon443-749Korea Department of Electrical and Computer Engineering University of Utah Asia CampusIncheon21985Korea Department of Artificial Intelligence Chungnam National UniversityDaejeon34134Korea

With the increase in IoT(Internet of Things)devices comes an inherent challenge of *** the world today,privacy is the prime concern of every *** one’s privacy and keeping anonymity throughout the system is a desired functionality that does not come without inevitable trade-offs like scalability and increased complexity and is always exceedingly difficult to *** challenge is keeping confidentiality and continuing to make the person innominate throughout the *** address this,we present our proposed architecture where we manage IoT devices using blockchain *** proposed architecture works on and off blockchain integrated with the closed-circuit television(CCTV)security camera fixed at the rental *** this framework,the CCTV security camera feed is redirected towards the owner and renter based on the smart contract *** entity(owner or renter)can see the CCTV security camera feed at one *** is no third-party dependence except for the CCTV security camera deployment *** contributions include the proposition of framework architecture,a novel smart contract algorithm,and the modification to the ring signatures leveraging an existing cryptographic *** are made based on different systems’security and key management *** an empirical study,our proposed algorithm performed better in key generation,proof generation,and verification *** comparing similar existing schemes,we have shown the proposed architectures’*** now,we have developed this system for a specific area in the real ***,this system is scalable and applicable to other areas like healthcare monitoring systems,which is part of our future work.

关键词： Privacy anonymity blockchain IoT smart contracts

Anomaly Detection in Imbalanced Encrypted Traffic with Few Packet Metadata-Based Feature Extraction

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Computer Modeling in Engineering & Sciences 2024年第10期141卷 585-607页

作者： Min-Gyu Kim Hwankuk Kim Department of Financial information Security Kookmin UniversitySeoul02707Republic of Korea Department of information Security Cryptography Mathematics Kookmin UniversitySeoul02707Republic of Korea

In the IoT(Internet of Things)domain,the increased use of encryption protocols such as SSL/TLS,VPN(Virtual Private Network),and Tor has led to a rise in attacks leveraging encrypted *** research on anomaly detection using AI(Artificial Intelligence)is actively progressing,the encrypted nature of the data poses challenges for labeling,resulting in data imbalance and biased feature extraction toward specific *** study proposes a reconstruction error-based anomaly detection method using an autoencoder(AE)that utilizes packet metadata excluding specific node *** proposed method omits biased packet metadata such as IP and Port and trains the detection model using only normal data,leveraging a small amount of packet *** makes it well-suited for direct application in IoT environments due to its low resource *** experiments comparing feature extraction methods for AE-based anomaly detection,we found that using flowbased features significantly improves accuracy,precision,F1 score,and AUC(Area Under the Receiver Operating Characteristic Curve)score compared to packet-based ***,for flow-based features,the proposed method showed a 30.17%increase in F1 score and improved false positive rates compared to Isolation Forest and ***,the proposedmethod demonstrated a 32.43%higherAUCwhen using packet features and a 111.39%higher AUC when using flow features,compared to previously proposed oversampling *** study highlights the impact of feature extraction methods on attack detection in imbalanced,encrypted traffic environments and emphasizes that the one-class method using AE is more effective for attack detection and reducing false positives compared to traditional oversampling methods.

关键词： One-class anomaly detection feature extraction auto-encoder encrypted traffic CICIoT2023

Varifocal occlusion in an optical see-through near-eye display with a single phase-only liquid crystal on silicon

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Photonics Research 2024年第4期12卷 833-853页

作者： WOONGSEOB HAN JAE-WON LEE JUNG-YEOP SHIN MYEONG-HO CHOI HAK-RIN KIM JAE-HYEUNG PARK Department of Electrical and Computer Engineering Inha University100 Inha-roMichuhol-guIncheon 22212Republic of Korea School of Electronic and Electrical Engineering Kyungpook National University80 Daehak-roBuk-guDaegu 41566Republic of Korea School of Electronics Engineering Kyungpook National University80 Daehak-roBuk-guDaegu 41566Republic of Korea Department of information and Communication Engineering Inha University100 Inha-roMichuhol-guIncheon 22212Republic of Korea

We propose a near-eye display optics system that supports three-dimensional mutual *** exploiting the polarization-control properties of a phase-only liquid crystal on silicon (LCoS),we achieve real see-through scene masking as well as virtual digital scene imaging using a single *** depth control of the real scene mask and virtual digital image is also achieved by using a focus tunable lens (FTL) pair of opposite *** proposed configuration using a single LCoS and opposite curvature FTL pair enables the self-alignment of the mask and image at an arbitrary depth without distorting the see-through view of the real *** verified the feasibility of the proposed optics using two optical benchtop setups:one with two off-the-shelf FTLs for continuous depth control,and the other with a single Pancharatnam–Berry phase-type FTL for the improved form factor.

关键词： optics crystal phase